1. Technical Field
The disclosed embodiments relate to transferring web searchers or browsers to particular landing pages following an ad click based on query or web page content and on characteristics of the landing pages, and more particularly, correlation of landing page type with conversion data provided by advertisers.
2. Related Art
In recent years, online advertising has become an economic force that sustains numerous Internet services, ranging from major web search engines to obscure blogs. The standard approach to textual web advertising is based on modeling the user's needs and interests, and using this model to find suitable advertisements (“ads”). In Web search, numerous studies have focused on classifying the query intent and on retrieving the most relevant ads. However, little research has been devoted to what actually happens after an ad is clicked, the subject of the embodiments disclosed herein.
A large part of the Web advertising market consists of textual ads, the ubiquitous short text messages usually marked as “sponsored links.” There are two main channels for distributing such ads. Sponsored search (or paid search advertising) places ads on the result pages of a web search engine, where ads are selected to be relevant to the search query. All major web search engines (Google, Microsoft, Yahoo!) support sponsored ads and act simultaneously as a web search engine and an ad search engine. Content match (or contextual advertising) places ads on third-party web pages based on subject matter content of those web pages. Today, almost all of the for-profit, non-transactional websites—those that do not directly sell anything—rely at least to some extent on contextual advertising revenue. Content match supports sites that range from individual bloggers and small niche communities to large publishers such as major newspapers. Herein, the focus is on sponsored search, but the classification of landing pages and correlation of conversion rates described below may be applied to content match as well.
Sponsored search includes interplay of three entities: advertisers, the search engine, and users or searchers that perform query search or simply browse. The advertiser provides the supply of ads. Usually the activity of the advertisers is organized around campaigns, which are defined by a set of ads with a particular temporal and thematic goal (e.g., sale of digital cameras during the holiday season). As in traditional advertising, the goal of the advertisers can be broadly defined as promotion of products or services. The search engine provides real estate for placing ads (e.g., allocates space on search results pages), and selects ads that are relevant to the user's query. Users visit the web pages and interact with the ads.
Sponsored search usually falls into the category of direct marketing (as opposed to brand advertising), that is, advertising whose aim is a direct response, where the effect of a campaign is measured by the user reaction (e.g., purchase of advertised goods or services). Compared to traditional media, one of the advantages of online advertising in general and sponsored search in particular is that it is relatively easy to measure the user response related thereto. Usually the desired immediate reaction is for the user to follow the link in the ad and visit the advertiser's website. However, the desired eventual outcome is for the user to perform a transaction on the advertised website, e.g., purchase a product or service being advertised. Therefore, evaluation methodology may be based on measuring conversion rate, which is the fraction of users who performed the advertised transaction among those who merely clicked on the advertisement.
The prevalent pricing model for textual ads is that the advertisers pay for every click on the advertisement (pay-per-click or “PPC”). There are also other models, such as pay-per-impression, where the advertiser pays for the number of exposures of an ad, and pay-per-action (“PPA”), where the advertiser pays only if the ad leads to a sale or similar completed transaction. In this paper we deal with the PPC model, which is most often used in practice.
The amount paid by the advertiser for each click is usually determined by an auction process. The advertisers place bids on a search phrase, and their position in the column of ads displayed on the search results page is determined by their bid. Thus, each ad is annotated with one or more bid phrases. In addition to the bid phrase, an ad also contains a title usually displayed in bold font, and a creative, which is a few lines of text, usually shorter than 120 characters, displayed on the page. Naturally, each ad contains a URL to the advertised web page, called the landing page.
In the model currently used by all the major search engines, bid phrases serve a dual purpose: they explicitly specify queries for which the ad should be displayed and simultaneously put a price tag on a click event. Obviously, these price tags could be different for different queries. For example, a contractor advertising his services on the Internet might be willing to pay a small amount of money when his ads are clicked from general queries such as home remodeling, but higher amounts if the ads are clicked from more focused queries such as hardwood doors or laminate flooring. Most often, ads are shown for queries that are expressly listed among the bid phrases for the ad, thus resulting in an exact match (i.e., identity) between the query and the bid phrase. However, it might be difficult (or even impossible) for the advertiser to list all the relevant queries ahead of time. Therefore, search engines can also analyze queries and modify them slightly in an attempt to match pre-defined bid phrases. This approach, called broad (or advanced) match, facilitates more flexible ad matching, but is also more error-prone, and only some advertisers opt for it. There are two bodies of prior research that are relevant to our study.
Online advertising is an emerging area of research, so the published literature is quite sparse. A recent study confirms the intuition that ads need to be relevant to the user's interest to avoid degrading the user's experience and increase the probability of reaction. In sponsored search, ads are triggered by the web search query, which is often just a few words long, and therefore selecting relevant ads based on such short input is difficult. One way to address this problem is to perform query expansion based on web search results, which can also be performed ahead of time for head (popular) and torso (rarer) queries.
There are several models of pricing online ads, which vary by the amount of risk shared by the advertiser and the publisher. Charging advertisers for ad displays (impressions) effectively places all of the risk with the advertiser, since the ads displayed might not even be relevant to the user. Charging in proportion to the conversion rate, which measures the proportion of users who actually committed to the advertised transaction, moves the risk almost entirely to the advertiser. Although many users perform a purchase in the same session when they click on the ad, many others will do so at a later time, having considered the worthiness of the transaction and conducting some research. In such cases, it becomes nearly impossible to relate the transaction to the initial ad click, making it very difficult to charge commensurately to the true conversion rate. The current practice of charging per click offers a middle ground between these two extremes, as paying per click lets the advertiser ascertain that the ad was at least somewhat relevant to the user, who expressed some interest by clicking on the ad. Due to this prevalence of charging per click, prior studies on forecasting user response to ads mostly focused on predicting the click-through rates based on estimated ad relevance as well as click history. In contrast, studies conducted herein focus on the true conversion rate.